In smart manufacturing, people are facing an increasing amount of industrial data derived
from various digitalized and connected sources in all kinds of formats. Analyzing and …

In meteorology, cluster analysis is frequently used to determine representative trends in
ensemble weather predictions in a selected spatio-temporal region, eg, to reduce a set of …

Despite their extensive use and the quality amelioration, CFRPs remain susceptible to a
variety of manufacturing defects such as the pores. Predictive tools capable of correlating …

The combination of long established techniques in morphometrics with novel shape
modeling approaches in geometry processing has opened new ways of visualizations of …

Summary open_iA is a platform for visual analysis and processing of volumetric datasets.
The main driver behind its development is to provide a common framework for performing …

Visual computing has become highly attractive for boosting research endeavors in the
materials science domain. Using visual computing, a multitude of different phenomena may …

Pores are the most common defect in carbon fiber reinforced plastics (CFRPs). Numerical
predictive tools capable of taking into account the porosity characteristics, as detected by …

We present a new visual analysis approach to support the comparative exploration of 2D
vector-valued ensemble fields. Our approach enables the user to quickly identify the most …

We examine visual representations of data that make use of combinations of both 2D and
3D data mappings. Combining 2D and 3D representations is a common technique that …

X-ray computed tomography (XCT) with flat-panel matrix detectors is a promising non-
destructive method to scan and characterize external and internal structures of a specimen …